key: cord-1011699-5mw7s4s2
authors: Azhdari Tehrani, Hamed; Ramezaninejad, Soodeh; Mardani, Masoud; Shokouhi, Shervin; Darnahal, Maryam; Hakamifard, Atousa
title: Hematologic malignancies and COVID‐19 infection: A monocenter retrospective study
date: 2022-05-22
journal: Health Sci Rep
DOI: 10.1002/hsr2.638
sha: ddbffd6d32606e38037951b7c60d8369351a411e
doc_id: 1011699
cord_uid: 5mw7s4s2

INTRODUCTION: Hematologic malignancies are risk factors for severe COVID‐19 infection. Identification of risk factors correlated with mortality in these groups of patients is important in the assessment strategy. We studied the characteristics of patients with hematologic malignancies and COVID‐19 and then analyzed the predictors of mortality. METHODS: Eligible for the analysis were hospitalized patients with hematologic malignancies and confirmed COVID‐19 infection observed between January 2020 and March 2021. Patients were categorized based on the type of malignancy and phase of the treatment. RESULTS: A total of 194 COVID‐19 infected patients with hematologic malignancies were included. The median age was 44 (15–81) years; 135 of them were males and 59 were females. Acute myeloid leukemia was the most frequent cancer type (43.8%). A total of 119 patients had severe COVID‐19 and 61 patients were admitted to the intensive care unit. A total of 92 deaths occurred in all cases for an overall case‐fatality rate of 47%. Male gender, preinduction and induction phase of the treatment, intensive care admission, low levels of oxygen saturation, Rhesus (RH) factor positivity, and higher fibrinogen level correlated with mortality. CONCLUSION: This study focuses on the epidemiology, risk factors, outcomes, and predictors of mortality of COVID‐19 among patients with hematologic malignancies. Patients with hematologic malignancies are at high risk of mortality.

Patients with hematological malignancies are at high risk of developing severe infections including COVID-19 because of immunodeficiency status due to underlying malignancy and immunosuppressive treatments. 1 In these patients, there are several issues, including comorbidities and compromised immune status, 2 which can promote or interfere with the classical course of COVID-19 infection.

These patients usually had one or several courses of chemotherapy that predispose them to pancytopenia. This phase of immunosuppression takes usually about 2-3 weeks, so viral infections and opportunistic infections can cause severe and life-threatening infections. On the other hand, COVID-19 promotes its infectivity through immune-related changes, especially cytokine release and also endothelial injury-related thrombotic reactions. Leukocyte and platelet counts are both decreased during chemotherapy, 3 so one of the hypotheses is that in patients with leukopenia and thrombocytopenia, cytokine release cannot promote inflammatory reactions and also endothelial injury. 4 In this study, we evaluated the characteristics of patients with hematologic malignancies and COVID-19 infection and analyzed the predictors of mortality. 

For each patient, demographic data, past medical history, comorbidities, chemotherapeutic regimens, and also the phase of the hematologic malignancy treatment, such as preinduction, induction, In this study, there were patients with acute myeloid leukemia (AML), acute lymphoid leukemia (ALL), Hodgkin and non-Hodgkin lymphoma (HL and NHL), multiple myeloma (MM), myelodysplastic syndromes (MDS), hairy cell leukemia (HCL), and hemophagocytic lymphohistiocytosis (HLH). We divided patients based on the treatment phase, namely preinduction, induction, consolidation, maintenance, and refractory. Preinduction refers to patients who were eligible to start chemotherapy; however, they had active COVID-19 disease and had not received any chemotherapeutic regimen. In the induction phase, patients had received chemotherapy; however, they became COVID-19 positive during the course of their chemotherapy or in the nadir phase of chemotherapy in which they had cytopenia. Consolidation refers to patients with AML, ALL in which patients were in postinduction phase of treatment. In the consolidation phase, patients usually were in remission for primary disease; however, if they had received chemotherapy recently, they had cytopenia.

Maintenance refers to long-term chemotherapy in patients with a remission state in ALL, AML-M3, and also MM. Also, we have noted CLL and lymphoma patients' induction and maintenance phases. In these patients, induction refers to first-time chemotherapy and maintenance refers to second, third, and more rounds of chemotherapy; however, they were responsive to treatments and were not refractory. Refractory patients were referred to patients that were unresponsiveness to any type of chemotherapy and had active disease. Patients who had criteria for hospitalization were managed according to National Institutes Of Health (NIH) COVID-19 guidelines based on disease severity.

Analyzed endpoints were frequency of COVID-19 among hematological patients, the severity of disease based on ICU admission, which therapies for COVID-19 they had received, assess preexisting comorbidities, outcomes of these patients, and length of hospital stay. Duration of hospitalization for COVID-19 infection was defined as the onset of clinical symptoms or the day with positive polymerase chain reaction (PCR) until the time of discharge from COVID-19 service. The case-fatality rate was defined as the proportion of deaths for any cause compared to the total number of patients.

Data were analyzed using the SPSS version 21.0 Statistical package (SPSS Inc.). Quantitative and qualitative data were presented as mean ± SD, median (minimum-maximum), and frequency (percentage). Data preparation were done based on the study protocol. Descriptive statistics were applied to explore and describe the data. The normality of continuous data was evaluated using the Kolmogorov-Smirnov test. We used the independent sample t-test and χ 2 (or fisher's exact test) for comparison between alive and deceased patients. Mann-Whitney nonparametric tests were applied for biomarkers analysis between two groups.

A binary logistic regression model was fitted to identify the associated parameters with mortality. Variables were selected primarily based on a theoretical conceptual framework predefined in the study proposal. Among the independent factors, which were candidates to be entered into the multivariable modeling, those with a p value of <0.3 were selected and entered into the statistical modeling procedure. A backward Wald elimination technique was applied for modeling. Accordingly, the odds ratio (OR) and its 95% confidence interval (CI) were estimated for each factor associated with mortality. Type I error was predefined at 0.05.

In this single-center retrospective study, we included 194 hospitalized patients with hematological malignancies and COVID-19

infection. Demographic and clinical characteristics were shown in (Table 1) . Chemotherapeutic regimens and mortality rates of each cancer type were shown in (Table 2 ) and an analysis of the variables was shown in (Table 3) .

T A B L E 1 Demographic and clinical characteristics based on gender of patients. Maintenance in lymphoma refers to second or more times chemotherapy. p Nivolumab (a PD-1 targeted therapy). q GEMOX (gemcitabine + oxaliplatin). r R-CHOP (rituximab + cyclophosphamide + doxorubicin + vincristine + prednisolone). s R-ICE (rituximab + ifosfamide + carboplatin + etoposide). t VCD (Bortezomib + cyclophosphamide + dexamethasone) u VRD (bortezomib + lenalidomide + dexamethasone). v VD (bortezomib + dexamethasone). w Preinduction in patients with MDS refers to patients who were indicated for chemotherapy (MDS with excess blast type) but did not receive chemotherapy.

x Induction in patients with MDS refers to patients who were indicated for chemotherapy (MDS with excess blast type).

T A B L E 3 Univariable Analysis of association between all parameters and mortality. cancer had a higher rate of mortality; however, recent cytotoxic chemotherapy did not have any impact on the outcome of these patients. 8 In a survey conducted by Lee et al., 9 those with cancers had higher age, higher comorbidities, and also majority were males and had more obesity. When they are older than 65 or when they are males rather than females, they have more positive PCR test. Milano et al. 10 showed that patients with a history of malignancy had 24% mortality rather than 3% mortality in patients without it. Also, these patients shed viral particles longer than others.

The overall mortality rate in this study was 47%, which is related especially to the preinduction and induction phases of the treatment.

However, patients with hematologic malignancies receive several chemotherapeutic agents, and also these patients, especially those who are not in the remission phase, are rendered to opportunistic infection and also COVID-19; hence, along with the several studies that we have mentioned in this section, it seems that the mortality for this group of patients with COVID-19 is much higher rather than other groups of patients. Conceptualization; investigation; methodology; supervision; writing -review and editing.

The authors declare no conflicts of interest.

The lead author (manuscript guarantor) affirms that this manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted;

and that any discrepancies from the study as planned (and, if relevant, registered) have been explained.

Hamed Azhdari Tehrani http://orcid.org/0000-0003-4419-4540

Atousa Hakamifard http://orcid.org/0000-0001-9456-2239

Note: Bold values Indicate statistical significance

Abbreviations: ALL, acute lymphoblastic leukemia

AML, acute myeloid leukemia; CLL, chronic lymphocytic leukemia; CRP, C-reactive protein; ESR, erythrocyte sedimentation rate

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